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The Memory Hierarchy II CPSC 321 Andreas Klappenecker.

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2 The Memory Hierarchy II CPSC 321 Andreas Klappenecker

3 Today’s Menu Cache Virtual Memory Translation Lookaside Buffer

4 Caches Why? How?

5 Memory Users want large and fast memories SRAM is too expensive for main memory DRAM is too slow for many purposes Compromise Build a memory hierarchy

6 Locality If an item is referenced, then it will be again referenced soon (temporal locality) nearby data will be referenced soon (spatial locality) Why does code have locality?

7 Mapping: address modulo the number of blocks in the cache, x -> x mod B Direct Mapped Cache

8 Cache with 1024=2 10 words tag from cache is compared against upper portion of the address If tag=upper 20 bits and valid bit is set, then we have a cache hit otherwise it is a cache miss What kind of locality are we taking advantage of? Direct Mapped Cache The index is determined by address mod 1024

9 Taking advantage of spatial locality: Direct Mapped Cache

10 Bits in a Cache How many total bits are required for a direct-mapped cache with 16 KB of data, 4 word blocks, assuming a 32 bit address? 16 KB = 4K words = 2^12 words Block size of 4 words => 2^10 blocks Each block has 4 x 32 = 128 bits of data + tag + valid bit tag + valid bit = (32 – 10 – 2 – 2) + 1 = 19 Total cache size = 2^10*(128 + 19) = 2^10 * 147 Therefore, 147 KB are needed for the cache

11 Cache Block Mapping Direct mapped cache a block goes in exactly one place in the cache Fully associative cache a block can go anywhere in the cache it is difficult to find a block parallel comparison to speed-up search Set associative cache a block can go to a (small) number of places compromise between the two extremes above

12 Cache Types

13 Set Associative Caches Each block maps to a unique set, the block can be placed into any element of that set, Position is given by (Block number) modulo (# of sets in cache) If the sets contain n elements, then the cache is called n-way set associative





18 Summary: Where can a Block be Placed? NameNumber of SetsBlocks per Set Direct mapped# Blocks in Cache1 Set associative (#Blocks in Cache) Associativity Associativity (typically 2-8) Fully associative1Number of blocks in cache

19 Summary: How is a Block Found? AssociativityNumber of Sets# Comparisons Direct mappedIndex1 Set associativeIndex the set, search among elements Degree of Associativity Fully associative search all cache entries size of the cache separate lookup table0

20 Virtual Memory

21 Processor generates virtual addresses Memory is accessed using physical addresses Virtual and physical memory is broken into blocks of memory, called pages A virtual page may be absent from main memory, residing on the disk or may be mapped to a physical page

22 Virtual Memory Main memory can act as a cache for the secondary storage (disk) Virtual address generated by processor (left) Address translation (middle) Physical addresses (right) Advantages: illusion of having more physical memory program relocation protection

23 Pages: virtual memory blocks Page faults: if data is not in memory, retrieve it from disk huge miss penalty, thus pages should be fairly large (e.g., 4KB) reducing page faults is important (LRU is worth the price) can handle the faults in software instead of hardware using write-through takes too long so we use writeback Example: page size 2 12 =4KB; 2 18 physical pages; main memory <= 1GB; virtual memory <= 4GB

24 Page Faults Incredible high penalty for a page fault Reduce number of page faults by optimizing page placement Use fully associative placement full search of pages is impractical pages are located by a full table that indexes the memory, called the page table the page table resides within the memory

25 Page Tables The page table maps each page to either a page in main memory or to a page stored on disk

26 Page Tables

27 Making Memory Access Fast Page tables slow us down Memory access will take at least twice as long access page table in memory access page What can we do? Memory access is local => use a cache that keeps track of recently used address translations, called translation lookaside buffer

28 Making Address Translation Fast A cache for address translations: translation lookaside buffer

29 Translation Lookaside Buffer Some typical values for a TLB TLB size 32-4096 Block size: 1-2 page table entries (4-8bytes each) Hit time: 0.5-1 clock cycle Miss penalty: 10-30 clock cycles Miss rate: 0.01%-1%

30 TLBs and Caches

31 More Modern Systems Very complicated memory systems:

32 Processor speeds continue to increase very fast — much faster than either DRAM or disk access times Design challenge: dealing with this growing disparity Trends: synchronous SRAMs (provide a burst of data) redesign DRAM chips to provide higher bandwidth or processing restructure code to increase locality use prefetching (make cache visible to ISA) Some Issues

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